Earlier, preventive maintenance for a vehicle largely relied on a visual inspection of the vehicle and its systems by a driver or an auto-mechanic, which invariably depended upon their experience. With development of electronic processors, vehicle diagnostic systems like onboard diagnostic system (OBD) for vehicle began to be widely used for fault-detection and scheduling vehicle maintenance. Currently the OBD systems are standard equipment on all the modern vehicles. The interfaces for current OBD system are governed by standards like SAE J1580 PWM/VPW, or ISO 15765 CAN, or SAE J2284-3. The information relating to the vehicle captured by the OBD play an important role in understanding factor affecting the performance of the vehicle and conditioning of the vehicle. At present the preventive maintenance are based on the historic OBD data collected and analysed by a model solely dependent on hardware of the vehicle.
With the introduction of freeways and speedways, the travel time reduced and commuting between places became easy. The use of freeways and speedways bought with it inherent need of continuous monitoring of the road condition, as a number of vehicle were travelling and at higher velocities. The road monitoring is essential because roadways and speedways are subjected to wear and tear, which hampers the travelling quality and in certain circumstances may result in irreparable harm.
The use of Global positioning systems (GPS) for assisting driver to plan his route also proved a viable solution for road monitoring, as the road condition became an important factor affecting the travel time and fuel management system. A modified apparatus comprising 3-axis accelerometer would provide the necessary inputs for determining the road condition. The apparatus needs to be oriented at a fixed position in order to compute the road conditions. Previously, the orientation correction was done using other supporting data/device such as magnetometer, gyroscope.
To overcome the limitation mentioned above US 2010/0318257 application discloses a method that calculates Euler's rotation angles and transforms the sampled values from a referred coordinate frame of a three-axis accelerometer device fixed to a vehicle to a reference coordinate frame of the vehicle. The method determines two rotation angles while the vehicle is stationary and assumed is not inclined with respect to gravity, so that only the transformed value corresponding to a vertical axis of the vehicle equals acceleration due to gravity. Then, data acquired from the sensors typically during a braking event and indicated by a vehicle diagnostic system, along with the other two rotation angles, are used in the first derivative of a second Euler's rotation equation to determine the remaining rotation angle. Data from the sensors is transformed by the three angles to the vehicle's coordinate frame and correlated with acceleration data derived from the diagnostic system to verify the rotation angles. The disclosure teaches the use of positioning system like GPS to capture the location of the vehicle and also takes into account the velocity of the vehicle to orient the accelerometer. The disclosure does not disclose the sampling frequency used to capture data.
A paper authored by Artis Mednis et. al. titled “Real Time Pothole Detection using Android Smartphone's With Accelerometers” discloses the use of a mobile sensing system for road irregularity detection using Android OS based smart-phones. The paper discloses use the use of a fixed accelerometer and a sampling frequency of 100 Hertz (Hz) to capture the related data. The use of higher sampling frequency increases the battery consumption, as computation scales up with higher amount of data coming from high sampling rate.
US 2011/0012720 application filed by Robert Hirschfeld discloses a system that integrates a smart phone or personal communication device (PCD) to capture plurality of data relating to the vehicle. The data is captured by various sensors and system mounted in the vehicle and the smart phone. The application discloses method to capture data relating to driving behaviour and responses of vehicle systems to the driving behaviour without accounting for road condition, which also affect the prognosis of the vehicle. The application assumes the orientation of the accelerometer is fixed.
From the reference cited, there is a long felt need for a system, a method and a device that is configured to dynamically orient an accelerometer without using any external device, enabling the accelerometer to capture a wide variety of data. There is a need in the art to develop a system for real time prognosis of vehicle, which takes into account all the factors affecting the vehicle condition.